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NAMEAlgorithm::Evolutionary::Op::Breeder - Even more customizable single generation for an evolutionary algorithm. SYNOPSIS use Algorithm::Evolutionary qw( Individual::BitString
Op::Mutation Op::Crossover
Op::RouletteWheel
Op::Breeder);
use Algorithm::Evolutionary::Utils qw(average);
my @pop;
my $number_of_bits = 20;
my $population_size = 20;
my $replacement_rate = 0.5;
for ( 1..$population_size ) {
my $indi = new Algorithm::Evolutionary::Individual::BitString $number_of_bits ; #Creates random individual
$indi->evaluate( $onemax );
push( @pop, $indi );
}
my $m = new Algorithm::Evolutionary::Op::Mutation 0.5;
my $c = new Algorithm::Evolutionary::Op::Crossover; #Classical 2-point crossover
my $selector = new Algorithm::Evolutionary::Op::RouletteWheel $population_size; #One of the possible selectors
my $generation =
new Algorithm::Evolutionary::Op::Breeder( $selector, [$m, $c] );
my @sortPop = sort { $b->Fitness() <=> $a->Fitness() } @pop;
my $bestIndi = $sortPop[0];
my $previous_average = average( \@sortPop );
$generation->apply( \@sortPop );
Base ClassAlgorithm::Evolutionary::Op::Base DESCRIPTIONBreeder part of the evolutionary algorithm; takes a population and returns another created from the first METHODSnew( $ref_to_operator_array[, $selector = new Algorithm::Evolutionary::Op::Tournament_Selection 2 ] )Creates a breeder, with a selector and array of operators apply( $population[, $how_many || $population_size] )Applies the algorithm to the population, which should have been evaluated first; checks that it receives a ref-to-array as input, croaks if it does not. Returns a sorted, culled, evaluated population for next generation. SEE ALSOMore or less in the same ballpark, alternatives to this one
CopyrightThis file is released under the GPL. See the LICENSE file included in this distribution, or go to http://www.fsf.org/licenses/gpl.txt
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